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Related papers: FeynGame-2.1 -- Feynman diagrams made easy

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In theories like SM or MSSM with a complex gauge group structure the complete set of Feynman diagrams contributed to a particular physics process can be splited to exact gauge invariant subsets. Arguments and examples given in the review…

High Energy Physics - Phenomenology · Physics 2009-11-07 E. E. Boos

The benefits of automating design cycles for Bayesian inference-based algorithms are becoming increasingly recognized by the machine learning community. As a result, interest in probabilistic programming frameworks has much increased over…

Machine Learning · Computer Science 2018-11-12 Marco Cox , Thijs van de Laar , Bert de Vries

Probabilistic graphical models (PGMs) serve as a powerful framework for modeling complex systems with uncertainty and extracting valuable insights from data. However, users face challenges when applying PGMs to their problems in terms of…

Machine Learning · Computer Science 2024-05-29 Jiantong Jiang , Zeyi Wen , Peiyu Yang , Atif Mansoor , Ajmal Mian

We present an improved version of our program package oneloop which -- written as a package for MAPLE -- solves one-loop Feynman integrals. The package is calculating one-, two- and three-point functions both algebraically and numerically…

High Energy Physics - Phenomenology · Physics 2009-10-30 L. Brücher , J. Franzkowski , D. Kreimer

We build on the recently proposed EigenGame that views eigendecomposition as a competitive game. EigenGame's updates are biased if computed using minibatches of data, which hinders convergence and more sophisticated parallelism in the…

Machine Learning · Statistics 2022-03-23 Ian Gemp , Brian McWilliams , Claire Vernade , Thore Graepel

In a recent paper \cite{ft} a new powerful method to calculate Feynman diagrams was proposed. It consists in setting up a Taylor series expansion in the external momenta squared. The Taylor coefficients are obtained from the original…

High Energy Physics - Phenomenology · Physics 2016-09-01 J. Fleischer , O. V. Tarasov

In the wake of the growing popularity of machine learning in particle physics, this work finds a new application of geometric deep learning on Feynman diagrams to make accurate and fast matrix element predictions with the potential to be…

Computational Physics · Physics 2022-11-29 Harrison Mitchell , Alexander Norcliffe , Pietro Liò

The aim of XLOOPS is to calculate one-particle irreducible Feynman diagrams with one or two closed loops for arbitrary processes in the Standard model of particles and related theories. Up to now this aim is realized for all one-loop…

High Energy Physics - Phenomenology · Physics 2009-10-30 L. Brücher , J. Franzkowski , D. Kreimer

Cyanure is an open-source C++ software package with a Python interface. The goal of Cyanure is to provide state-of-the-art solvers for learning linear models, based on stochastic variance-reduced stochastic optimization with acceleration…

Machine Learning · Statistics 2019-12-23 Julien Mairal

This MATLAB program calculates the dynamics of the reduced density matrix of an open quantum system modeled by the Feynman-Vernon model. The user gives the program a vector describing the coordinate of an open quantum system, a hamiltonian…

Quantum Physics · Physics 2015-06-05 Nikesh S. Dattani

Programming techniques which extend the capabilities of FeynArts and FormCalc are introduced and explained using examples from real applications.

High Energy Physics - Phenomenology · Physics 2009-11-11 T. Hahn , J. I. Illana

LevelScheme is a scientific figure preparation system for Mathematica. The main emphasis is upon the construction of level schemes, or level energy diagrams, as used in nuclear, atomic, molecular, and hadronic physics. LevelScheme also…

Computational Physics · Physics 2007-05-23 M. A. Caprio

In this article we introduce the supervised machine learning tool called Feyn. The simulation engine that powers this tool is called the QLattice. The QLattice is a supervised machine learning tool inspired by Richard Feynman's path…

Webs are sets of Feynman diagrams that contribute to the exponents of scattering amplitudes, in the kinematic limit in which emitted radiation is soft. As such, they have a number of phenomenological and formal applications, and offer…

High Energy Physics - Phenomenology · Physics 2016-02-17 C. D. White

fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks. The toolkit is based on PyTorch and…

Computation and Language · Computer Science 2019-04-03 Myle Ott , Sergey Edunov , Alexei Baevski , Angela Fan , Sam Gross , Nathan Ng , David Grangier , Michael Auli

This paper is an introduction to the language of Feynman Diagrams. We use Reshetikhin-Turaev graphical calculus to define Feynman diagrams and prove that asymptotic expansions of Gaussian integrals can be written as a sum over a suitable…

Quantum Algebra · Mathematics 2013-09-30 Domenico Fiorenza , Riccardo Murri

This work introduces a new software package `Sesame' for the numerical computation of classical semiconductor equations. It supports 1 and 2-dimensional systems and provides tools to easily implement extended defects such as grain…

Applied Physics · Physics 2019-05-01 Benoit Gaury , Yubo Sun , Peter Bermel , Paul M. Haney

We present the Feynman integral reduction program Kira 1.2 and describe its new features and other changes w.r.t. the previous versions. The main new features include a much faster equation generator, more flexible seed specification…

High Energy Physics - Phenomenology · Physics 2018-12-05 Philipp Maierhöfer , Johann Usovitsch

Citation graph visualisation is a useful tool for contextual awareness in academic research. Unfortunately, existing solutions can suffer from several drawbacks, such as a poor scaling, shallow network traversal, freemium gating, and slow…

Digital Libraries · Computer Science 2025-12-30 Harry Ballington

We show that momentum space Feynman diagrams involving internal massless fields can be cast as conformal integrals. This leads to a classification of all Feynman diagrams into conformal families, labelled by conformal integrals. Computing…

High Energy Physics - Theory · Physics 2025-01-03 Siddharth G. Prabhu
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